Jumping Genes for Water Distribution System Optimization

The design of a water distribution system (WDS) is a challenging problem involving multiple conflicting objectives. The goal of multi-objective WDS design optimization is to find the set of solutions which embodies the Pareto-optimal trade-off between system cost and benefit (typically some measure of reliability). This provides decision-makers with a broad understanding of design possibilities, allowing them to identify a solution with the maximum cost-benefit, or maximize benefit subject to a given budget. A WDS must be designed in order to satisfy consumer demand at required pressures, handle multiple demand loading conditions, withstand component failure and degradation, and provide surplus capacity for growth. In this paper, a jumping-gene (JG) evolutionary algorithm is applied to multi-objective WDS design, and tested on a number of established WDS benchmarks. The JG algorithm is compared to the Non-dominating Sorting Genetic Algorithm II (NSGA-II). Results indicate that the JG algorithm is comparable to the NSGA-II, yet sufficiently different to warrant consideration, particularly in terms of finding high reliability looped configurations. It is argued that the JG mechanism is capable of mimicking how an engineer might exchange capacity between various parts of a system in the course of the design process, and as such is able to find robust alternative designs which may elude competing algorithms.